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Welcome to

Neuromorphic and Biomedical Engineering Laboratory

National Tsing Hua University, Taiwan

News

Our Recent News

Yen-Wen Chen, Rui-Hsuan Wang, Yu-Hsiang Cheng, Chih-Cheng Lu, "SUN: Dynamic Hybrid-Precision SRAM-Based CIM Accelerator with High Macro Utilization Using Structured Pruning Mixed-Precision Networks", TCAD, accepted

Posted by NBME on 02 19, 2024

Yu Hsuan Lin, Chao Yang Tang, Kea-Tiong Tang, “A 0.2-pJ/Sop Digital Spiking Neuromorphic Processor with Temporal Parallel Dataflow and Efficient Synapse Memory Compression”, 2024 IEEE 6th AICAS, accepted for Lecture presentation.

Posted by NBME on 02 19, 2024

Chia-Hua Hsu, Yu-Wei Lin, Yi-Hsin Liao, Liang-Kai Wang, Cheng-Jung Tsai, Kea-Tiong Tang, "A Low-Noise, Low-Power Neural Signal Amplifier for Deep Brain Stimulation System Chips Tolerating 3V Stimulation", 2024 IEEE ISCAS, accepted for Lecture presentation.

Posted by NBME on 01 16, 2024

賀 ! 本實驗室專題生楊士賢、余駿越、林允仲同學榮獲 112學年度「智慧感知聯網中心大專生專題競賽 影片人氣獎」

Posted by NBME on 12 15, 2023

實驗室目前以三大核心計畫為研究方向,各組以2~4位碩士生帶領數名專題生,對於實驗室有興趣的同學,可以參考專題說明投影片(pdf)

Posted by NBME on 11 23, 2023

Tang, C. L., Chou, T. I., Yang, S. R., Lin, Y. J., Ye, Z. K., Chiu, S. W., Tang, K. T. (2023) “Development of a Nondestructive Moldy Coffee Beans Detection System Based on Electronic Nose”, IEEE Sensors Letters, 7(2), 1-4., accepted.

Posted by NBME on 11 23, 2023

賀 ! 本實驗室廖一心同學榮獲 112學年度「電機系碩、博士班入學成績優異獎學金」

Posted by NBME on 10 26, 2023

Ya-Han Fan, Ting-I Chou, Shih-Wen Chiu, Kea-Tiong Tang, “Gas Prediction Method Based on Dynamic Response Analysis of Metal Oxide Sensors under Temperature Modulation”, IEEE SENSORS 2023, accepted.

Posted by NBME on 10 22, 2023

Mu-Hsiang Kao, Shih-Wen Chiu, Meng-Rui Lee, Min Sun, Kea-Tiong Tang, “Deep Neural Network of E-Nose Sensor for Lung Cancer Classification”, 2023 IEEE Biosensors, 134438, accepted.

Posted by NBME on 10 22, 2023

Research

Artificial Intelligence, Electronic Nose and Biomedical Implants

Artificial Intelligence

System Design

Neuromorphic AI Accelerator System Design

Algorithm Design

Neuromorphic AI Inference Chip Algorithm

Chip Design

Neuromorphic AI Accelerator Chip Design

Electronic Nose

Miniature Electronic Nose System

Integrated Micro Sensor Array

System-on-Chip and Package

Module, System and Algorithm

Application: Early Screening of Diseases

Chest physician

Gas analysis method

Diagnosis chip (VAP, COPD, LC)

Biomedical Implants

Circuit Design for Biomedical Devices

Data Transceiver, Wireless Power Transfer System, Stimulator

Analog to Digital Converter, Low Noise Amplifier, Digital Processor

Application: Deep Brain Stimulation

Implantable, Batteryless, Bidirectional Communications

Low Power Neural Recording and Stimulation

Small Device Size

Publication

Recent Publications

A Concentration-based Drift Calibration (CDC) Transfer Learning Method for Gas Sensor Array Data

 The practical use of electronic nose (e-nose) systems suffers from drift issue, which alters data distribution and reduces the accuracy of classification. This letter proposes a transfer learning method called concentration-based drift calibration (CDC) for calibrating the sensor drift. Based on the sensor characteristic that sensor response is correspondent to gas concentration, transfer samples were collected in the target domain for certain gas concentrations and then used for calibration with a designed concentration-based model and CDC transfer process. This method was evaluated on a complex time-varying drift dataset. The experimental results show that the proposed method for drift calibration is effective and can be used for real-world applications. Moreover, the CDC transfer process can be applied over time with data that has been previously collected to yield a more generalized model.

A Fully Integrated High-Power-Supply-Rejection Linear Regulator with an Output-Supplied Voltage Reference

 This study proposes an output capacitor-less linear regulator with high power supply rejection (PSR) for a wireless power transmission system. To achieve high PSR with a noisy input voltage, a fully integrated linear regulator with its reference circuit supplied by the output voltage is proposed. The proposed technique can isolate the reference circuit from the noisy VIN, thereby reducing the requirements of the conventional bulky lowpass filter loading the reference voltage node while achieving superior PSR performance. The regulator uses an N-type pass transistor and a dual-feedback structure to achieve wideband ripple-filtering and fast transient responses. The proposed regulator is compatible with typical biomedical implants requiring a 10mA load current at 1.1V output voltage while consuming a total quiescent current of 276µA. A PSR performance was measured to be −48 and −56 dB against the VIN and charge pump at 10 MHz, respectively. The unity gain bandwidth (UGB) of the regulator was 291MHz. The proposed regulator was fabricated using commercial TSMC 0.18-µm CMOS technology with an area of 0.1054 mm2 including the reference circuit.

Contact

Contact Us

 kttang@ee.nthu.edu.tw
 +886-3-5162178
 +886-3-571597
 R812, Delta Building,Dept. of Electrical Engineering,
  National Tsing Hua University,No. 101, Sec. 2, Kuang-Fu
  Road, Hsinchu 30013, Taiwan